Triple

T2655870
Position Surface form Disambiguated ID Type / Status
Subject Kyoto Station E54607 entity
Predicate architect P184 FINISHED
Object Hiroshi Hara E338497 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hiroshi Hara | Statement: [Kyoto Station, architect, Hiroshi Hara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hiroshi Hara
Context triple: [Kyoto Station, architect, Hiroshi Hara]
  • A. Hiroshi Hara chosen
    Hiroshi Hara is a prominent Japanese architect known for his innovative, futuristic designs and influential urban projects in Japan and abroad.
  • B. Hara Takashi
    Hara Takashi was a Japanese politician who became the first commoner to serve as Prime Minister of Japan during the early Taishō period.
  • C. Takeo Fujisawa
    Takeo Fujisawa was a Japanese businessman who played a pivotal role in building Honda into a global automotive and motorcycle powerhouse through his leadership and management expertise.
  • D. Masujiro Hashimoto
    Masujiro Hashimoto was a pioneering Japanese industrialist and automotive engineer best known as the founder of what would become Nissan Motor Company.
  • E. Kakuei Tanaka
    Kakuei Tanaka was a powerful and controversial Japanese prime minister and political kingmaker who dominated postwar politics through his influence within the Liberal Democratic Party.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd933ec008190aef1442460c4cfbc completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69b511f37d188190b5604645960e3f11 completed March 14, 2026, 7:44 a.m.
Created at: March 6, 2026, 9:53 p.m.